def main():
parser = argparse.ArgumentParser(
formatter_class = argparse.RawTextHelpFormatter)
parser.add_argument('--operation', type = str, default = "all", help = "[all | extract_tree | train | metric]")
parser.add_argument('--conf', type = str, default = "default")
parser.add_argument('--metric_input', type = str, default = "new_train_res")
parser.add_argument('--train_output', type = str, default = str(int(time.time() * 1000.0)))
parser.add_argument('--metric_output', type = str, default = str(int(time.time() * 1000.0)))
args = parser.parse_args()
params = dh.load_json_file(os.path.join(CONF_PATH, args.conf + ".json"))
params["metric_input"] = os.path.join(RES_PATH, args.metric_input)
params["train_output"] = os.path.join(RES_PATH, "train_res_" + args.train_output)
params["metric_output"] = os.path.join(RES_PATH, "metric_res_" + args.metric_output)
if args.operation == "all":
train_model(params)
metric(params)
elif args.operation == "extract_tree":
extract_tree(params)
elif args.operation == "train":
train_model(params)
elif args.operation == "metric":
metric(params)
else:
print "Not Support!"
def loop(params, G, embeddings, weights, metric, output_path, draw):
embeddings_path = os.path.join(RES_PATH, params["embeddings_path"])
dynamic_embeddings = dh.load_json_file(embeddings_path)
for items in dynamic_embeddings:
embeddings = np.array(items["embeddings"])
metric(embeddings)
draw(embeddings)
def main():
parser = argparse.ArgumentParser(
formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument('--operation',
type=str,
default="all",
help="[all | train | metric | draw]")
parser.add_argument('--conf', type=str, default="default")
parser.add_argument('--iteration', type=int, default=10001)
parser.add_argument('--model', type=str, default="model_simple")
args = parser.parse_args()
params = dh.load_json_file(
os.path.join(SINGLE_CONF_PATH, args.conf + ".json"))
params["iteration"] = args.iteration
params["model"] = args.model
if args.operation == "all":
train_model(params)
metric(params)
elif args.operation == "train":
train_model(params)
elif args.operation == "metric":
metric(params)
elif args.operation == "draw":
pass
else:
print "Not Support!"
def main_old():
parser = argparse.ArgumentParser(
formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument('--operation',
type=str,
default="all",
help="[all | init | train | metric | draw]")
parser.add_argument('--conf', type=str, default="default")
args = parser.parse_args()
params = dh.load_json_file(os.path.join(CONF_PATH, args.conf + ".json"))
metric_path_pre = os.path.join(RES_PATH, args.conf)
if os.path.exists(metric_path_pre) == False:
os.mkdir(metric_path_pre)
output_path = os.path.join(metric_path_pre, dh.get_time_str())
metric_path = output_path + "_metric"
def metric(embeddings):
if "metrics" not in params:
return
for metric in params["metrics"]:
res = getattr(Metric, metric["func"])(embeddings, metric)
dh.append_to_file(metric_path, str(res) + "\n")
print res
dh.symlink(metric_path, os.path.join(metric_path_pre, "new_metric"))
if "drawers" in params:
draw_path = output_path + "_draw"
if os.path.exists(draw_path) == False:
os.mkdir(draw_path)
draw_cnt = [0]
def draw(embeddings):
if "drawers" not in params:
return
for drawer in params['drawers']:
getattr(Metric, drawer["func"])(embeddings, drawer, draw_path,
draw_cnt[0])
draw_cnt[0] += 1
if args.operation == "all":
G, embeddings, weights = __import__("init." + params["init"]["func"],
fromlist=["init"]).init(
params["init"], metric,
output_path, draw)
__import__("dynamic_loop." + params["main_loop"]["func"],
fromlist=["dynamic_loop"]).loop(params["main_loop"], G,
embeddings, weights, metric,
output_path, draw)
elif args.operation == "init":
G, embeddings, weights = __import__("init." + params["init"]["func"],
fromlist=["init"]).init(
params["init"], metric,
output_path, draw)
elif args.operation == "draw":
pass
else:
print "Not Support!"
def main():
parser = argparse.ArgumentParser(
formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument('--conf', type=str, default="default")
args = parser.parse_args()
params = dh.load_json_file(
os.path.join(MULTI_CONF_PATH, args.conf + ".json"))
out_path = os.path.join(RES_PATH,
"multi_res_" + str(int(time.time() * 1000.0)))
single_params = {}
for item in params.items():
if item[0] == "models":
continue
single_params[item[0]] = item[1]
for m in params["models"]:
for it in m.items():
if it[0] == "traversal":
continue
else:
single_params[it[0]] = it[1]
if "traversal" not in m:
tmp = []
else:
tmp = [item for item in m["traversal"].items()]
with open(out_path, "a") as f:
dfs(tmp, single_params, f)
try:
os.symlink(out_path, os.path.join(RES_PATH, "MultiRes"))
except OSError:
os.remove(os.path.join(RES_PATH, "MultiRes"))
os.symlink(out_path, os.path.join(RES_PATH, "MultiRes"))
def init(params, metric, output_path, draw):
embeddings_path = os.path.join(RES_PATH, params["embeddings_path"])
dic = dh.load_json_file(embeddings_path)
embeddings = np.array(dic["embeddings"])
metric(embeddings)
draw(embeddings)
return None, None, None
def main():
parser = argparse.ArgumentParser(
formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument('--operation',
type=str,
default="all",
help="[all | init | train]")
parser.add_argument('--conf', type=str, default="amherst0.25")
args = parser.parse_args()
params = dh.load_json_file(os.path.join(CONF_PATH, args.conf + ".json"))
fw = open('my_embedding.txt', 'w')
metric_path_pre = os.path.join(RES_PATH, args.conf)
if os.path.exists(metric_path_pre) == False:
os.mkdir(metric_path_pre)
output_path = os.path.join(metric_path_pre, dh.get_time_str())
print(output_path)
metric_path = output_path + "_metric"
def metric(embeddings):
if "metrics" not in params:
return
for metric in params["metrics"]:
print("[] Start node classification...")
res = getattr(Metric, metric["func"])(embeddings, metric)
dh.append_to_file(metric_path, str(res) + "\n")
print("[+] Metric: " + str(res))
dh.symlink(metric_path, os.path.join(metric_path_pre, "new_metric"))
if args.operation == "all":
G, embeddings, weights = __import__("init." + params["init"]["func"],
fromlist=["init"]).init(
params["init"], metric,
output_path)
__import__("dynamic_loop." + params["main_loop"]["func"],
fromlist=["dynamic_loop"]).loop(params["main_loop"], G,
embeddings, weights, metric,
output_path)
print(embeddings)
elif args.operation == "init":
G, embeddings, weights = __import__("init." + params["init"]["func"],
fromlist=["init"]).init(
params["init"], metric,
output_path)
else:
print("Not Support!")